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Record W2139749203 · doi:10.5897/jpbcs.9000101

Participatory selection and characterization of quality protein maize (QPM) varieties in Savanna agro- ecological region of DR-Congo

2010· article· en· W2139749203 on OpenAlexaff
Mbuya Kankolongo, K. K. Nkongolo, A. Kalonji-Mbuyi, Roger Vumilia Kizungu

Bibliographic record

VenueJournal of Plant Breeding and Crop Science · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsLaurentian University
Fundersnot available
KeywordsBiologyAgronomyYield (engineering)Selection (genetic algorithm)CropAgricultureZea maysCitizen journalismQuality (philosophy)BiotechnologyEcology

Abstract

fetched live from OpenAlex

Maize (Zea mays L.) is a major cereal crop for human nutrition in the Democratic Republic of Congo (DR- Congo). Prevailing normal maize is deficient in two essential amino acids, lysine and tryptophan. Participatory variety selection was applied to select diversified quality protein maize (QPM) varieties that possess farmers’ preferred plant and grain traits. The varieties were planted with and without chemical fertilization. Selection was based primarily on agronomic traits such as time to maturity, plant and ear aspect, disease and insect resistance, yield and yield components as well as flour quality. There were significant differences among QPM varieties for several agronomic traits. The use of participatory approach in agricultural research allowed selection of one QPM, (QPMSRSYNTH), and one normal improved maize (AK9331-DMR-ESR-Y) for their yield advantage over currently released normal maize varieties in more than one criterion. The adoption of these newly introduced varieties is expected to be high since they were selected based on farmer’s preference.   Key words: Quality protein maize, participatory varietal selection, DR-Congo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.120

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.250
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2010
Admission routes1
Has abstractyes

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